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Record W3194195016 · doi:10.1002/ana.26200

Brain Structure and Degeneration Staging in Friedreich Ataxia: <scp>Magnetic Resonance Imaging</scp> Volumetrics from the <scp>ENIGMA‐Ataxia</scp> Working Group

2021· article· en· W3194195016 on OpenAlexaff
Ian H. Harding, Sidhant Chopra, Filippo Arrigoni, Sylvia Boesch, Arturo Brunetti, Sirio Cocozza, Louise A. Corben, Andreas Deistung, Martin B. Delatycki, Stefano Diciotti, Imis Dogan, Stefania Evangelisti, Marcondes C. França, Sophia Göricke, Nellie Georgiou‐Karistianis, Laura Ludovica Gramegna, Pierre‐Gilles Henry, Carlos R. Hernandez‐Castillo, Diane Hutter, Neda Jahanshad, James M. Joers, Christophe Lenglet, Raffaele Lodi, David Neil Manners, Alberto Martínez, Andrea Martinuzzi, Chiara Marzi, Mario Mascalchi, Wolfgang Nachbauer, Chiara Pane, Denis Peruzzo, Pramod Kumar Pisharady, Giuseppe Pontillo, Kathrin Reetz, Thiago Junqueira Ribeiro de Rezende, Sandro Romanzetti, Francesco Saccà, Christoph Scherfler, Jörg B. Schulz, Ambra Stefani, Claudia Testa, Sophia I. Thomopoulos, Dagmar Timmann, Stefania Tirelli, Caterina Tonon, Marinela Vavla, Gary F. Egan, Paul M. Thompson

Bibliographic record

VenueAnnals of Neurology · 2021
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsDalhousie University
FundersNational Institute of Biomedical Imaging and BioengineeringNational Health and Medical Research CouncilMedical Research CouncilNational Institutes of Health
KeywordsCerebellumBrainstemWhite matterDentate nucleusAtaxiaMagnetic resonance imagingNeuroscienceRed nucleusPathologyPsychologyMedicineAnatomyNucleusRadiology

Abstract

fetched live from OpenAlex

Objective Friedreich ataxia (FRDA) is an inherited neurological disease defined by progressive movement incoordination. We undertook a comprehensive characterization of the spatial profile and progressive evolution of structural brain abnormalities in people with FRDA. Methods A coordinated international analysis of regional brain volume using magnetic resonance imaging data charted the whole‐brain profile, interindividual variability, and temporal staging of structural brain differences in 248 individuals with FRDA and 262 healthy controls. Results The brainstem, dentate nucleus region, and superior and inferior cerebellar peduncles showed the greatest reductions in volume relative to controls (Cohen d = 1.5–2.6). Cerebellar gray matter alterations were most pronounced in lobules I–VI ( d = 0.8), whereas cerebral differences occurred most prominently in precentral gyri ( d = 0.6) and corticospinal tracts ( d = 1.4). Earlier onset age predicted less volume in the motor cerebellum ( r max = 0.35) and peduncles ( r max = 0.36). Disease duration and severity correlated with volume deficits in the dentate nucleus region, brainstem, and superior/inferior cerebellar peduncles ( r max = −0.49); subgrouping showed these to be robust and early features of FRDA, and strong candidates for further biomarker validation. Cerebral white matter abnormalities, particularly in corticospinal pathways, emerge as intermediate disease features. Cerebellar and cerebral gray matter loss, principally targeting motor and sensory systems, preferentially manifests later in the disease course. Interpretation FRDA is defined by an evolving spatial profile of neuroanatomical changes beyond primary pathology in the cerebellum and spinal cord, in line with its progressive clinical course. The design, interpretation, and generalization of research studies and clinical trials must consider neuroanatomical staging and associated interindividual variability in brain measures. ANN NEUROL 2021;90:570–583

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.039
GPT teacher head0.273
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations66
Published2021
Admission routes1
Has abstractyes

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